Quality Assurance & Standards Data Analyst, Financial Crime Analytics

NatWest Group; Lakenheath; On-site; GBP 40,000 - 55,000; Full time

Job summary

A leading financial services company in Lakenheath is seeking a Quality Assurance & Standards Data Analyst to enhance business understanding through advanced analytics. This role involves delivering data solutions, collaborating with stakeholders, and simplifying analytics insights. Proficiency in SAS, Teradata, Snowflake, or Python coding is essential. Strong communication skills and financial services knowledge are required for success in this position.

Qualifications

• Demonstrated proficiency in advanced analytics and SQL.
• Experience translating data insights for stakeholders.
• Good understanding of data management principles.

Responsibilities

• Define business questions supported by advanced analytics.
• Work in Agile teams, coordinating resources.
• Deliver analytics solutions bringing customer value.
• Communicate data opportunities to stakeholders.

Skills

Proficiency in SAS

Proficiency in Teradata

Proficiency in Snowflake

Proficiency in Python coding

Strong communication skills

Knowledge of data visualization tools like Tableau

Financial services knowledge

Job description

Join us as a Quality Assurance & Standards Data Analyst, Financial Crime Analytics

• This is an opportunity to take on a purpose-led role in a newly formed Quality Assurance and Standards Analytics team
• You’ll be consulting with our stakeholders to understand their needs and identify suitable data and analytics solutions to meet them along with business challenges in line with our purpose
• You’ll bring proficiency in SAS, Teradata, Snowflake or Python coding

What you'll do

As a Quality Assurance & Standards Data Analyst, you’ll be using advanced analytics to develop business solutions which increase the understanding of our business, including its customers, processes, channels and products. You’ll be working closely with business stakeholders to define detailed business questions, problems or opportunities which can be supported through advanced analytics, making sure that new and existing processes are designed to be efficient, simple and automated where possible.

As well as this, you’ll be:

• Working in an Agile way within multi-disciplinary data and analytics teams, co-ordinating resources from across the team and the business to achieve agreed project and scrum outcomes
• Delivering data and analytics expertise and solutions, which brings commercial and customer value to business challenges
• Communicating data and analytics opportunities and bringing them to life in a way that business stakeholders can understand and engage with, supporting them to select the best approach for the business needs
• Using new tools, technologies and methodologies to carry out advanced analytics
• Sharing relevant updates with key stakeholders bringing together advanced analytics, data science and data engineering work that is easily understandable and links back clearly to our business needs

The skills you'll need

We’re looking for someone with a passion for data and analytics together with knowledge of data architecture, data analysis, key tooling, SQL and other relevant coding languages. Along with proficiency in advanced analytics, you’ll bring an ability to simplify data into clear data visualisations and compelling insight using appropriate systems and tooling such as Tableau. You’ll also have good financial services knowledge, and the ability to identify wider business impact, risk and opportunities, making connections across key outputs and processes.

You’ll also demonstrate:

• Proficiency in SAS, Teradata, Snowflake or Python coding
• Domain knowledge of NatWest Financial Crime and Customer Due Diligence and Data related Processes
• Familiarisation with the end to end Customer Due Diligence customer journey through to PKYC and ongoing InLife customer management
• Strong knowledge of data management principles
• Experience of translating data and insights for key stakeholders
• Knowledge of data engineering, data science and decisioning disciplines
• Strong communication skills with the ability to engage with a wide range of stakeholders